Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …

Recent years have seen an increasing interest in Demand Response (DR) as a means to
provide flexibility, and hence improve the reliability of energy systems in a cost-effective way …

The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

Due to increasing complexity, uncertainty and data dimensions in power systems,
conventional methods often meet bottlenecks when attempting to solve decision and control …

Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

This paper proposes a novel framework for home energy management (HEM) based on
reinforcement learning in achieving efficient home-based demand response (DR). The …

The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …

In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …

The rapidly increasing penetration of distributed energy resources (DERs) calls for a
hierarchical framework where aggregating entities handle the energy management …

Demand response (DR) is an effective means to help maintain the balance between power
supply and demand, promote energy conservation and emission reduction. Nevertheless …